论文标题
随机网络具有异质互惠
Random Networks with Heterogeneous Reciprocity
论文作者
论文摘要
社交网络的用户表现出多样化的行为和在线习惯。例如，用户回复帖子的趋势可能取决于用户和发布的人。为了方便起见，我们将用户分组为汇总的行为模式，重点关注回复或回报消息的趋势。社交网络中的互惠功能反映了用户之间的信息交换。我们研究具有异质互惠水平的优先依恋模型的性质，给出模型边缘计数的增长率，并证明了经验程度频率与限制分布的收敛性。这种限制分布不仅是多元定期变化的，而且具有隐藏的常规变化的属性。
Users of social networks display diversified behavior and online habits. For instance, a user's tendency to reply to a post can depend on the user and the person posting. For convenience, we group users into aggregated behavioral patterns, focusing here on the tendency to reply to or reciprocate messages. The reciprocity feature in social networks reflects the information exchange among users. We study the properties of a preferential attachment model with heterogeneous reciprocity levels, give the growth rate of model edge counts, and prove convergence of empirical degree frequencies to a limiting distribution. This limiting distribution is not only multivariate regularly varying, but also has the property of hidden regular variation.
